CN110225112A - Information mutually enjoys platform between a kind of hospital based on SaaS - Google Patents
Information mutually enjoys platform between a kind of hospital based on SaaS Download PDFInfo
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- CN110225112A CN110225112A CN201910492568.2A CN201910492568A CN110225112A CN 110225112 A CN110225112 A CN 110225112A CN 201910492568 A CN201910492568 A CN 201910492568A CN 110225112 A CN110225112 A CN 110225112A
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/10—Network architectures or network communication protocols for network security for controlling access to devices or network resources
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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Abstract
The present invention relates to information exchanging visit systems between a kind of hospital based on SaaS platform, including tenant's management module, tenant's module, multi-tenant memory module, big data analysis module.The platform relies on each tenant's computer system, and information is mutually enjoyed between can be realized hospital.Meanwhile the division mode of more sparse tables in multi-tenant data storage model will also be improved, can significantly more efficient management store tenant data, rationally utilize resource, improve the closeness of data storage.At present due to various regions level of economic development difference, the unbalanced of medical resource is caused, medical information is not flowed, wasted seriously, and the present invention can rely on Modernized Information Technology to realize that basic hospital information is mutually enjoyed, the primary care level of IT application is promoted, medical resource is more reasonably utilized.
Description
Technical field
The invention belongs to computer data field of storage, information mutually enjoys platform between being related to a kind of hospital based on SaaS.
Background technique
With the development of science and technology, information technology becomes the emphasis direction of current social research, all trades and professions are all being made
Informationization, the informationization for promoting industry can effectively promote the competitiveness of industry, improve the working efficiency of practitioner, promote
The development of society, medical field is even more so, and China various regions economic development difference results in medical treatment development extremely imbalance, base
The development that medical information level is obviously out of step with the times, and there is also following several situations: the flowing of personnel, and personnel
Medical treatment information and medical treatment historical record but without and then flowing, personnel have arrived other place and have seen a doctor, and many things may
It operates one time, often results in a waste of resources and time again；Patient has arrived nearest A hospital, and there is no suitable for discovery
The doctor of drug, Medical Devices or counterpart, therefore he must shift hospital, be on earth farther center large hospital or
The B hospital closer from A hospital is gone to, but and whether the uncertain hospital next gone is also a lack of the drug of needs, medical treatment is set
Standby or counterpart doctor, this has just been highlighted in medical field, the importance of information sharing, even more so for base.
Therefore in order to improve the medical information degree and shared level of base, while self-condition, that is, cost of base is contemplated that
The problem of, it would be desirable to one is found both using Modernized Informatization Management and the suitable scheme of cost.
In this case, SaaS become we build the information sharing platform towards basic hospital it is optional it
Road, SaaS are the abbreviations of Software as a Service, mean that software services, and can provide software by internet and answer
With service, its maximum feature is that user need not develop software, buys hardware facility, do not have to building-up work computer room, less
With employing professional, it is only necessary to pay expense to ISP, so that it may pass through internet use information system.
Many software meetings in recent years and report also indicate that in the development in Software Industry future, SaaS will be primary study
Direction.On the one hand in order to solve the problems, such as in primary care that information is isolated, the level of informatization is low, on the other hand reduce construction at
This, and the function that existing solution considers at present is not comprehensive, and therefore, the present invention is provided between a kind of hospital based on SaaS
The management platform that information is mutually enjoyed.
Summary of the invention
In view of this, the purpose of the present invention is to provide the platform that information is mutually enjoyed between a kind of hospital based on SaaS, for
The problem of primary care condition is limited and plant maintenance, can be with more appropriate cost, and information is mutually enjoyed between realizing hospital, simultaneously
Using the calculating analysis ability of existing big data analysis system, possess highest data query permission, comprehensive analysis hospital
More valuable information is obtained with the data of patient and feeds back to patient, and furthermore the present invention will also improve SaaS flat surface and rent morely to
Sparse table division methods when user data stores, it is more efficient to use limited medical resource.
In order to achieve the above objectives, the invention provides the following technical scheme:
Information mutually enjoys platform, including tenant's management module, tenant's module, multi-tenant data between a kind of hospital based on SaaS
Memory module and big data analysis system；
Tenant's management module is used to be managed tenant, including the maintenance of charges, module, log, power
Limit management and prestige grading function；
Tenant's module includes function management module, user management module and tenant customization module, the function management
Module includes equipment management submodule, transaction record submodule, medication management submodule, and the user management module includes case history
Archives submodule, patient information submodule, information about doctor submodule, doctor recommend submodule and disease forecasting submodule；It is described
Tenant customization module includes the other function module that tenant customizes according to demand；
The multi-tenant data memory module is for storing each tenant's self information data and its subordinate's user information number
According to；
The big data analysis system carries out big data analysis for obtaining each tenant and user data.
Further, the big data analysis system is used to obtain each tenant in multi-tenant data memory module and its use
User data excavates user's history case history and medication history, carries out disease forecasting to user, and result feedback is sub to disease forecasting
In module；It is also used to analyze hospital equipment, drug, doctor and itself medical record information and recommends in conjunction with hospital position most suitable out
Hospital and doctor, result feedback under tenant's module doctor recommend submodule in.
Further, the data under tenant's module are divided into private data and non-private data type, and rely on and be based on
RBAC permission accesses to control the permission of checking of registrant, the private data of tenant is not checked by other tenants and user, each to rent
Family can share respective noncore data such as information about doctor, and the case history archive etc. of user, big data analysis system, which possesses, checks institute
There is the permission of data.
Further, the storage inside model of the data memory module of multi-tenant is the more sparse tables divided using improved procedure
Carry out tissue multi-tenant data, for already present multi-tenant data, more sparse tables use improved model split, by improvement side
More sparse tables that formula divides can be improved packing density, promote access performance, and by taking the table of 500 column as an example, 500 column are completely full
Foot uses, and partiting step includes:
S1: customized information (tenant data columns) T of existing multi-tenant is counted1{t1,t2,…,tn(from small to large)；
S2: in conjunction with having there is experience: it is poor to show apparent performance with projection 200 for DBMS 10 column of projection in the table of 500 column
Away from, also there is gap with the column of projection 100, and 200 column of projection and 300 column performance gaps of projection are smaller, therefore the data choosing in S1
The data lower than 100 are selected out, form array T2{t1,t2,…,ti, then the data lower than 200 but greater than 100 are selected, it is formed
Array T3{ti+1,ti+2,…,tj, residue is greater than 200 data, forms array T4(general seldom in practice), it is unified to draw into 500
The big table of column；
S3: to array T2, T3Carry out refinement and T2Division density should be greater than T3, that is, give array T2It is big to divide breakpoint number
In T3；
S4: T is calculated2{t1,t2,…,tiTwo adjacent datas difference, formed 1 { Δ of array Δ1,Δ2,…,Δi-1, i.e.,
Δ1=t2-t1, descending from array Δ 1 successively to select preceding m biggish number { Δs1a,Δ1b..., then T can be given2
Breakpoint is divided, is successively t1a, t1b..., and it is understood that t1a<ti；
S5: equally to T3Also the operation carried out above obtains array Δ 2, descending from array Δ 2 successively to select preceding n
A biggish number { Δ1a,Δ1b..., finally give T3Breakpoint is divided, is successively t from big to small2a,t2b..., and it is understood that
ti<t2a；
S6: the breakpoint marked off above is the columns of multiple sparse tables, and the quantity of list, with m, the value of n
It constitutes, and m > n；
By previous step, constitutes new division mode and on the one hand meet columns compared with cell refinement, the larger area of columns is roughened
On the other hand empirical rule also preferably can suitably be concluded data, packing density is promoted.
When further, for new tenant customization demand, be contemplated that the later period extends, thus new tenant with it is ready-portioned sparse
It is matched between table using the thought of redundancy, matching step includes:
S1: the custom tabular number C of new tenant is inputted；
S2: list number C is compared with breakpoint above respectively, obtains difference, and all differences are carried out absolute value
Processing；
S3: the corresponding breakpoint t of selection least absolute valuex, work as tx< C, then C should just be assigned to tx+1The list of columns, but
Consider amount of redundancy γ, meets tx+1- C > γ, then tx+1Meet distribution to require, if tx+1- C < γ, then actually by
It is assigned to tx+2In the table of columns；
S4: work as txWhen > C, if meeting tx- C > γ, then txMeet distribution to require, if tx+1- C > γ, then
Actually it is assigned to tx+1In the table of columns, consider that amount of redundancy is advantageous in that avoid data migrates again.
The beneficial effects of the present invention are:
1, the big data analysis system that the present invention includes possesses the highest permission for checking data, excavates the history number of patient
According to disease forecasting of the realization to patient；The combination doctor for analyzing hospital equipment, drug, doctor and itself medical record information and innovating
Institute's distance recommends most suitable hospital and doctor out.
2, multi-tenant data storage model of the invention contains a kind of improved sparse table division methods, being capable of more adduction
Reason utilizes computer resource, improves access performance；And when matching sparse table for new tenant customization, in conjunction with the thought of redundancy,
Avoid the migration again of tenant data.
3, the present invention is the information platform based on SaaS, and cost is relatively low, and the IT personnel for also not needing many professions go to safeguard,
It is limited to be very suitable to condition, the lower basic hospital of the level of informatization can significantly improve the medical condition of Countryside.
Other advantages, target and feature of the invention will be illustrated in the following description to a certain extent, and
And to a certain extent, based on will be apparent to those skilled in the art to investigating hereafter, Huo Zheke
To be instructed from the practice of the present invention.Target of the invention and other advantages can be realized by following specification and
It obtains.
Detailed description of the invention
To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention is made below in conjunction with attached drawing excellent
The detailed description of choosing, in which:
Fig. 1 is the overall structure diagram that information mutually enjoys platform between the hospital of the present invention based on SaaS；
Fig. 2 is that information mutually enjoys platform level configuration diagram between the hospital of the present invention based on SaaS；
Fig. 3 is division sparse table method flow diagram in multi-tenant back-end data storage model of the present invention.
Specific embodiment
Illustrate embodiments of the present invention below by way of specific specific example, those skilled in the art can be by this specification
Other advantages and efficacy of the present invention can be easily understood for disclosed content.The present invention can also pass through in addition different specific realities
The mode of applying is embodied or practiced, the various details in this specification can also based on different viewpoints and application, without departing from
Various modifications or alterations are carried out under spirit of the invention.It should be noted that diagram provided in following embodiment is only to show
Meaning mode illustrates basic conception of the invention, and in the absence of conflict, the feature in following embodiment and embodiment can phase
Mutually combination.
Wherein, the drawings are for illustrative purposes only and are merely schematic diagrams, rather than pictorial diagram, should not be understood as to this
The limitation of invention；Embodiment in order to better illustrate the present invention, the certain components of attached drawing have omission, zoom in or out, not
Represent the size of actual product；It will be understood by those skilled in the art that certain known features and its explanation may be omitted and be in attached drawing
It is understood that.
The same or similar label correspond to the same or similar components in the attached drawing of the embodiment of the present invention；It is retouched in of the invention
In stating, it is to be understood that if there is the orientation or positional relationship of the instructions such as term " on ", "lower", "left", "right", "front", "rear"
To be based on the orientation or positional relationship shown in the drawings, be merely for convenience of description of the present invention and simplification of the description, rather than indicate or
It implies that signified device or element must have a particular orientation, be constructed and operated in a specific orientation, therefore is described in attached drawing
The term of positional relationship only for illustration, is not considered as limiting the invention, for the ordinary skill of this field
For personnel, the concrete meaning of above-mentioned term can be understood as the case may be.
As shown in Figure 1, information mutually enjoys platform between a kind of hospital based on SaaS, including tenant's management module, tenant's module,
Multi-tenant data memory module and big data analysis system；Tenant Ji Ge hospital, platform, which rides in, participates in the tenant i.e. meter of hospital
In calculation machine system,
Tenant's management module is used to be managed tenant, including the maintenance of charges, module, log, power
Limit management and prestige grading function；These functions realize the management to subordinate tenant, for example prestige grading function can be to management
Tenant is regularly graded, and the good tenant that keeps up one's credit for a long time can obtain more economical lease expenses.
Tenant's module includes function management module, user management module and tenant customization module, the function management
Module includes equipment management submodule, transaction record submodule, medication management submodule, and the user management module includes case history
Archives submodule, patient information submodule, information about doctor submodule, doctor recommend submodule and disease forecasting submodule；It is each to rent
After the rental service of family, personal settings can be carried out outside basic public function and formulate respective required function module, that is, are rented
Family customized module, tenant after accomplishing the setting up, account distribute to user；Multi-tenant data memory module is for storing each tenant certainly
Body information data and its subordinate's user information data；
The big data analysis system carries out big data analysis for obtaining each tenant and user data.
As shown in Fig. 2, the platform is Three-tider architecture framework, it is boundary layer, application service layer, data respectively from top to bottom
Layer.Result from boundary layer to user display operation feedback and receive user operation commands, application service layer handles user
Input request, processing result are transmitted to boundary layer, and data Layer stores the relevant information of each tenant, and data resource passes through application clothes
Layer be engaged in meet the request command on upper layer.
Optionally, the big data analysis system is used to obtain each tenant in multi-tenant data memory module and its use
User data excavates user's (patient) history case history and medication history, carries out disease forecasting to user, and result is fed back to disease
It predicts in submodule；It is also used to analyze hospital equipment, drug, doctor and itself medical record information and recommends in conjunction with hospital position
Most suitable hospital and doctor, result feedback are recommended in submodule to the doctor under tenant's module.Additional description, for combining
Hospital's location information recommends hospital doctor, and allow for following situation: patient has arrived nearest A hospital, and there is no close for discovery
The doctor of suitable drug, Medical Devices or counterpart, therefore he must shift hospital, but it is transferred to farther but preferable hospital
Still closer but general hospital is gone to, if patient is emergency treatment, at this moment our analysis system will not only consider Hospital medical feelings
Condition is it should also be taken into account that the taken time problem of transfer process.
Optionally, the data under tenant's module are divided into private data and non-private data type, such as each tenant (doctor
Institute) equipment, drug belong to secret, information about doctor, case history archive etc. belong to non-secret.And it relies on and is based on RBAC permission addressing machine
It makes to control the permission of registrant, the private data of tenant is not checked by other tenants and user, and each tenant can share respectively non-
Private data such as information about doctor, the case history archive etc. of user, big data analysis system possess the permission for checking all data.
Optionally, the storage inside model of the data memory module of multi-tenant is the more sparse tables divided using improved procedure
Carry out tissue multi-tenant data, as shown in figure 3, being directed to already present multi-tenant data, more sparse tables use improved model split,
It can be improved packing density by more sparse tables that improved procedure divides, promoting access performance, (by taking the table of 500 column as an example, 500 are arranged
Fully meet use), the partiting step of improved procedure includes:
S101: customized information (tenant data columns) T of existing multi-tenant is counted1{t1,t2,…,tn(from small to large)；
S102: in conjunction with having there is experience: it is poor to show apparent performance with projection 200 for DBMS 10 column of projection in the table of 500 column
Away from, also there is gap with the column of projection 100, and 200 column of projection and 300 column performance gaps of projection are smaller, therefore the data choosing in S1
The data lower than 100 are selected out, form array T2{t1,t2,…,ti, then the data lower than 200 but greater than 100 are selected, it is formed
Array T3{ti+1,ti+2,…,tj, residue is greater than 200 data, forms array T4(general seldom in practice), it is unified to draw into 500
The big table of column；
S103: to array T2, T3Carry out refinement and T2Division density should be greater than T3, that is, give array T2Breakpoint number is divided to want
Greater than T3；
S104: T is calculated2{t1,t2,…,tiTwo adjacent datas difference, formed 1 { Δ of array Δ1,Δ2,…,Δi-1,
That is Δ1=t2-t1, descending from array Δ 1 successively to select preceding m biggish number { Δs1a,Δ1b..., then
To T2Breakpoint is divided, is successively t1a,t1b..., and it is understood that t1a<ti；
S105: equally to T3Also the operation carried out above obtains array Δ 2, descending from array Δ 2 successively to select
Preceding n biggish number { Δs1a,Δ1b..., finally give T3Breakpoint is divided, is successively t from big to small2a, t2b..., and we know
Road ti< t2a；
S106: the breakpoint marked off above is the columns of multiple sparse tables, and the quantity of list, and with m, n's is taken
Value is constituted, and m > n；
By previous step, constitutes new division mode and on the one hand meet columns compared with cell refinement, the larger area of columns is roughened
On the other hand empirical rule also preferably can suitably be concluded data, packing density is promoted.
When optionally, for new tenant customization demand, be contemplated that the later period extends, thus new tenant with it is ready-portioned sparse
It is matched between table using the thought of redundancy, matching step includes:
S201: the custom tabular number C of new tenant is inputted；
S202: list number C is compared with breakpoint above respectively, obtains difference, and all differences are carried out absolutely
Value processing；
S203: the corresponding breakpoint t of selection least absolute valuex, work as tx< C, then C should just be assigned to tx+1The list of columns,
But considers amount of redundancy γ, meet tx+1- C > γ, then tx+1Meet distribution to require, if tx+1- C < γ, then actually
It is assigned to tx+2In the table of columns；
S204: work as txWhen > C, if meeting tx- C > γ, then txMeet distribution to require, if tx+1- C > γ, that
Actually it is assigned to tx+1In the table of columns, consider that amount of redundancy is advantageous in that avoid data migrates again.
Finally, it is stated that the above examples are only used to illustrate the technical scheme of the present invention and are not limiting, although referring to compared with
Good embodiment describes the invention in detail, those skilled in the art should understand that, it can be to skill of the invention
Art scheme is modified or replaced equivalently, and without departing from the objective and range of the technical program, should all be covered in the present invention
Scope of the claims in.
Claims (5)
1. information mutually enjoys platform between a kind of hospital based on SaaS, it is characterised in that: including tenant's management module, tenant's module,
Multi-tenant data memory module and big data analysis system；
Tenant's management module is used to be managed tenant, including the maintenance of charges, module, log, permission pipe
Reason and prestige grading function；
Tenant's module includes function management module, user management module and tenant customization module, the function management module
Including equipment management submodule, transaction record submodule, medication management submodule, the user management module includes case history archive
Submodule, patient information submodule, information about doctor submodule, doctor recommend submodule and disease forecasting submodule；The tenant
Customized module includes the other function module that tenant customizes according to demand；
The multi-tenant data memory module is for storing each tenant's self information data and its subordinate's user information data；
The big data analysis system carries out big data analysis for obtaining each tenant and user data.
2. information mutually enjoys platform between the hospital according to claim 1 based on SaaS, it is characterised in that: the big data point
Analysis system is used to obtain each tenant and its user data in multi-tenant data memory module, excavates user's history case history and use
Medicine history carries out disease forecasting to user, and by result feedback into disease forecasting submodule；Be also used to analyze hospital equipment,
Drug, doctor and itself medical record information simultaneously recommend most suitable hospital and doctor out in conjunction with hospital position, and result feedback arrives
Doctor under tenant's module recommends in submodule.
3. information mutually enjoys platform between the hospital according to claim 1 based on SaaS, it is characterised in that: tenant's module
Under data be divided into private data and non-private data type, and rely on and accessed based on RBAC permission to control checking for registrant
Permission, the private data of tenant are not checked that each tenant can share respective noncore data, big data point by other tenants and user
Analysis system possesses the permission for checking all data.
4. information mutually enjoys platform between the hospital according to claim 1 based on SaaS, it is characterised in that: the data of multi-tenant
The storage inside model of memory module is more sparse tables using improved procedure division come tissue multi-tenant data, for existing
Multi-tenant data, more sparse tables use improved model split, by improved procedure divide more sparse tables can be improved number
According to density, access performance is promoted, if table has 500 column, partiting step includes:
S1: the customized information of existing multi-tenant, i.e. tenant data columns T are counted1{t1,t2,…,tn}；
S2: in conjunction with having there is experience: DBMS 10 column of projection in the table of 500 column show apparent performance gap with projection 200, with
100 column of projection also have gap, and 200 column of projection and 300 column performance gaps of projection are smaller, therefore the data in S1 are selected and are lower than
100 data form array T2{t1,t2,…,ti, then the data lower than 200, greater than 100 are selected, form array T3{ti+1,
ti+2,…,tj, residue is greater than 200 data, forms array T4, unified to draw the big table into 500 column；
S3: to array T2, T3Carry out refinement and T2Division density be greater than T3, that is, give array T2It divides breakpoint number and is greater than T3；
S4: T is calculated2{t1,t2,…,tiTwo adjacent datas difference, formed 1 { Δ of array Δ1,Δ2,…,Δi-1, i.e. Δ1=
t2-t1, descending from array Δ 1 successively to select preceding m biggish number { Δs1a,Δ1b..., give T2Breakpoint is divided, successively
It is t1a,t1b..., t1a<ti；
S5: to T3Also it carries out operation identical with step S4 and obtains array Δ 2, it is descending from array Δ 2 successively to select preceding n
A biggish number { Δ1a,Δ1b..., finally give T3Breakpoint is successively t from big to small2a,t2b..., ti<t2a；
S6: step S4, the breakpoint that S5 is marked off is the columns of multiple sparse tables, and the quantity of list, with m, the value of n
It constitutes, and m > n.
5. information mutually enjoys platform between the hospital according to claim 1 based on SaaS, it is characterised in that: fixed for new tenant
When demand processed, to consider that the later period extends, so matched between new tenant and ready-portioned sparse table using the thought of redundancy,
Its matching step includes:
S1: the custom tabular number C of new tenant is inputted；
S2: list number C is compared with breakpoint above respectively, obtains difference, and all differences are carried out absolute value processing；
S3: the corresponding breakpoint t of selection least absolute valuex, work as tx< C, then C is just assigned to tx+1The list of columns, but consider redundancy
γ is measured, t is metx+1- C > γ, then tx+1Meet distribution to require, if tx+1- C < γ, then be assigned to tx+2In the table of columns；
S4: work as txWhen > C, if meeting tx- C > γ, then txMeet distribution to require, if tx+1- C > γ, then be assigned to
tx+1In the table of columns.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110853760A (en) * | 2019-11-12 | 2020-02-28 | 好人生（上海）健康科技有限公司 | Interactive system for providing health guidance based on disease diagnosis |
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